1. Field of the Invention
The present disclosure relates to a cloud system for supporting a big data process, and an operation method thereof. More particularly, the present invention relates to a cloud system for continuously maintaining big data processing performance, and an operation method thereof.
2. Description of Related Art
The term “cloud” refers to a computing technology based on the Internet wherein a user can use web-based software services while a program therefor is executed in a utility data server accessed via the Internet.
Cloud services are generally classified as an IaaS (Infrastructure as a Service), a PaaS (Platform as a Service), and a SaaS (Software as a Service).
IaaS provides an infrastructure in the cloud means services proving a resource such as a server to a user. Amazon web services (AWS) is a representative example IaaS.
PaaS means a technology in which a user is a developer, and environments for developing software are provided. An APP engine of Google is a representative example of PaaS.
SaaS mean a technology of providing web-based application services, and N-drive of Naver, Dropbox, etc. are representative examples of SaaS.
Meanwhile, a cloud system may generate a virtual machine (VM) by dividing a physical computing resource. A big data system may be implemented and operated in a guest OS of the virtual machine of the cloud system. Accordingly, the big data system may be operated based on a resource (CPU, memory, disk, network, etc.) assigned by the cloud system.
In order to provide cloud services, a hypervisor that helps to install a virtual OS in a physical server and a cloud management system that helps a cloud environment management while interchanging information of a virtual machine resource may be required. As a cloud resource management system, a cloud stack and an open stack are provided.
Recently, a Hadoop that is widely used for a data analysis system is configured with a HDFS (Hadoop distributed file system) and a MapReduce.
A MapReduce processes data in two steps. A map modifies data by reading an input file in lines, a reduce collects result data of the map. Herein, a data modification rule of the map may be freely defined by a user.
A Hadoop builds and operates a cluster to analyze data, and a YARN (yet another resource negotiator) is used for monitoring and analyzing a Hadoop cluster resource to smoothly use a computing resource.
In a convention cloud resource management system, load-balancing, auto-scaling, and high availability (HA) are provided. Services in a cloud resource management system are functions for web-based services, thus it is not proper for other service as a big data.
The foregoing is intended merely to aid in the understanding of the background of the present invention, and is not intended to mean that the present invention falls within the purview of the related art that is already known to those skilled in the art.